Principal Machine Learning Engineer

PayPal

Hybrid

Quick summary

Work type
Hybrid
Location
San Jose, CA
Salary
$242,000–$359,150 / yr
Posted
81 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $226k
This role $301k
$157k most similar roles pay here $381k

This role pays more than 93% of similar roles. Most pay $194,500–$256,750 — the shaded band above. At the midpoint, this role pays about $301k versus about $226k for comparable roles.

Based on 240 similar postings.

Employer

About PayPal

PayPal is a leading global digital wallet and online payment system, founded in 1998, that allows individuals and businesses to send, receive, and manage funds securely in over 200 markets.

PayPal currently has 84 open roles on FindRole.

Listed pay typically runs $160,500–$235,826 across 84 roles with salary data.

Most-posted roles

View all roles at PayPal

At a glance

TL;DR · Principal Machine Learning Engineer

As a Senior Machine Learning Engineer at PayPal in San Jose, you will lead the strategic vision and development of advanced machine learning models to address complex business challenges. Your responsibilities include driving ML initiatives across multiple teams, optimizing state-of-the-art algorithms, and publishing research findings. You will also develop new methodologies and frameworks for ML applications, focusing on recommendation systems, search ranking, and personalization at consumer scale. The ideal candidate has over 10 years of experience in ML engineering with expertise in learning-to-rank, contextual bandits, and real-time recommendations serving millions of users. Strong skills in social platform ML, graph-based models, data engineering tools like BigQuery, Spark, and Airflow, as well as feature stores and model serving infrastructure are essential for this role.

What you'll do

  • Define and drive strategic vision for machine learning initiatives across multiple teams.
  • Lead development and optimization of state-of-the-art machine learning models.
  • Publish research findings and contribute to industry discussions on ML advancements.
  • Develop new methodologies and frameworks for scalable ML applications.
  • Build ML systems that significantly impact business metrics like engagement and retention.

What we're looking for

  • 10+ years of experience in ML engineering with expertise in recommendation systems and search ranking.
  • Deep production experience with learning-to-rank, contextual bandits, and real-time recommendation systems for millions of users.
  • Proven track record of building ML that drives business metrics such as engagement, conversion, and retention.
  • Experience leading the development of social platform ML including feed ranking and content discovery.
  • Strong skills in platform design, including feature stores, model serving, and experiment infrastructure.
  • Expertise in graph-based ML techniques like social graph embeddings and transaction graphs.
  • Proficient in data engineering with tools such as BigQuery, Spark, Airflow, and dbt.

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